U.S. patent number 8,773,289 [Application Number 12/730,594] was granted by the patent office on 2014-07-08 for runway condition monitoring.
This patent grant is currently assigned to The Boeing Company. The grantee listed for this patent is Jeanne C. Maggiore, Wayne R. Majkowski, Kevin L. Swearingen. Invention is credited to Jeanne C. Maggiore, Wayne R. Majkowski, Kevin L. Swearingen.
United States Patent |
8,773,289 |
Maggiore , et al. |
July 8, 2014 |
Runway condition monitoring
Abstract
A method and apparatus are present for monitoring a runway. Data
is received about the runway from a number of sensors associated
with an aircraft while the aircraft performs an operation on the
runway. A number of conditions are identified for the runway using
the data received from the number of sensors.
Inventors: |
Maggiore; Jeanne C. (Wildwood,
MO), Majkowski; Wayne R. (Florissant, MO), Swearingen;
Kevin L. (Saint Charles, MO) |
Applicant: |
Name |
City |
State |
Country |
Type |
Maggiore; Jeanne C.
Majkowski; Wayne R.
Swearingen; Kevin L. |
Wildwood
Florissant
Saint Charles |
MO
MO
MO |
US
US
US |
|
|
Assignee: |
The Boeing Company (Chicago,
IL)
|
Family
ID: |
44021771 |
Appl.
No.: |
12/730,594 |
Filed: |
March 24, 2010 |
Prior Publication Data
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Document
Identifier |
Publication Date |
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US 20130127642 A1 |
May 23, 2013 |
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Current U.S.
Class: |
340/947; 701/9;
340/580; 701/14; 340/425.5; 701/15; 340/963; 340/972; 340/951;
340/948; 340/971; 340/438; 340/945; 340/962 |
Current CPC
Class: |
G08G
5/065 (20130101); G08G 5/025 (20130101); G08G
5/0091 (20130101); G08G 5/0021 (20130101); G08G
5/0065 (20130101); G08G 5/0008 (20130101) |
Current International
Class: |
G08G
5/00 (20060101); G01C 21/00 (20060101); B60Q
1/00 (20060101); G08B 19/02 (20060101); G08B
21/00 (20060101); G05D 1/00 (20060101); G01C
5/00 (20060101); G06G 7/00 (20060101); G06F
19/00 (20110101); G06F 7/70 (20060101); B64F
1/20 (20060101); G08B 23/00 (20060101) |
Field of
Search: |
;340/947,945,958,959,961,962 |
References Cited
[Referenced By]
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|
Primary Examiner: Wu; Daniel
Assistant Examiner: Terrell; Emily C
Attorney, Agent or Firm: Yee & Associates, P.C.
Claims
What is claimed is:
1. A method for monitoring a runway, the method comprising:
receiving data about the runway from a number of sensors associated
with an aircraft while the aircraft performs an operation on the
runway; processing the data received from the number of sensors,
wherein the processing is performed by a data processing system in
the aircraft to produce processed data; determining a number of
conditions are present on the runway using the processed data; and
making predictions about the number of conditions present on the
runway or other conditions that may develop on the runway at a
future time using prognostic algorithms, the number of conditions,
and historical data, wherein the data processing system makes the
predictions, wherein the predictions include a rate of growth of a
condition on the runway.
2. The method of claim 1 further comprising: sending the number of
conditions to a location remote to the aircraft.
3. The method of claim 2, wherein the aircraft is a first aircraft
and the location is selected from one of a second aircraft and an
air traffic controller.
4. The method of claim 1, wherein the aircraft is a first aircraft
and further comprising: controlling operation of a second aircraft
using the runway after the first aircraft based on the number of
conditions.
5. The method of claim 1, wherein the number of sensors being
associated with the aircraft further comprises the number of
sensors being mounted on an underside of a fuselage of the
aircraft.
6. The method of claim 1, wherein the data received from the number
of sensors includes at least one of imaging data, radar data, light
detection and ranging data, camera data, or infrared data.
7. The method of claim 1, wherein the step of receiving the data
about the runway from the number of sensors comprises: identifying
a braking distance for the aircraft braking on the runway;
determining that a condition in the number of conditions is present
when the braking distance is greater than specified distance.
8. The method of claim 7 further comprising: determining whether
the condition in the number of conditions is present when a
directional vector of the aircraft and a directional vector of a
wheel on the aircraft are different.
9. The method of claim 1, wherein the number of conditions are
selected from at least one of an inconsistency in the runway, a
debris, an indentation, or a plant growth extending onto the
runway.
10. The method of claim 2, wherein the location is a surface
friction database.
11. The method of claim 1 further comprising: updating a
navigational chart with the number of conditions.
12. An apparatus comprising: a number of sensors associated with an
aircraft, wherein the number of sensors is configured to generate
data about a runway while the aircraft performs an operation on the
runway; a computer system in the aircraft, wherein the computer
system is configured to receive the data from the number of
sensors, process the data received from the number of sensors to
produce processed data, determine a number of conditions present on
the runway using the processed data, and make predictions about the
number of conditions present on the runway or other conditions that
may develop on the runway at a future time using prognostic
algorithms, the number of conditions, and historical data, wherein
the data processing system makes the predictions, wherein the
predictions include a rate of growth of a condition on the
runway.
13. The apparatus of claim 12, wherein the aircraft is a first
aircraft and wherein the computer system is further configured to
control operation of a second aircraft using the runway after the
first aircraft using the number of conditions.
14. The apparatus of claim 12, wherein the number of sensors being
associated with the aircraft further comprises the number of
sensors being mounted on an underside of a fuselage of the
aircraft.
15. The method of claim 1, wherein the data processing system uses
situational awareness to determine the number of conditions using
the processed data.
16. The method of claim 15, wherein the situational awareness
comprises aircraft operational data or weather data.
17. The method of claim 15, wherein the situational awareness
comprises a combination of temperature data, weather data,
airspeed, weight on wheels of the aircraft, angle of attack of the
aircraft, weather forecast data.
18. The method of claim 1 further comprising: determining whether a
condition in the number of conditions is present when a directional
vector of the aircraft and a directional vector of a wheel on the
aircraft are different.
19. The method of claim 1, wherein processing the data received
from the number of sensors comprises: filtering the data, wherein
filtering comprises removing noise from the data, and checking
validity of the data; and extracting features from the data,
wherein extracting the features from the data comprises performing
a transform on the data.
20. The method of claim 1, wherein processing the data received
from the number of sensors results in a numerical representation,
and wherein determining a number of conditions are present on the
runway using the processed data includes comparing the numeral
representation with a predetermined value to determine whether a
particular type of data indicates the presence of a type of
condition on the runway.
Description
BACKGROUND INFORMATION
1. Field
The present disclosure relates generally to an improved data
processing system, and more specifically to an improved data
processing system for monitoring a runway.
2. Background
Runways are areas commonly used for aircraft to travel during
takeoff, while traveling on the ground, and during landing. As used
herein, runways also include taxiways. Runways are frequently paved
with a material that supports the aircraft as the aircraft travels
over the runway. For example, the runway may reduce the amount of
shock absorbed by the aircraft while traveling over the runway, as
opposed to traveling over bare earth.
Conditions that develop on runways vary with weather and other
phenomenon. For example, snow may accumulate on a runway until the
snow melts or the snow is cleared by a plow or snow-melting agent.
Other conditions that develop on runways include, for example,
without limitation, standing water, slush, ice, debris,
indentations, and plant growth that extends onto the runway. In
other examples, inconsistencies develop in the runway. For example,
a pothole may develop in the runway due to a combination of a
snow-melting agent and frequent use by aircraft. In another
example, inconsistencies develop in the runway due to one or more
objects impacting the runway.
Conditions for a runway are noted by pilots of aircraft that are
using the runway or by equipment at an airport. The pilots or
equipment operators communicate the conditions for the runway to
air traffic controllers. In some examples, the air traffic
controllers inform other aircraft in the geographic area of the
conditions or update a database of conditions with the information
received from the pilots.
Therefore, it would be desirable to have a method and apparatus
that may overcome one or more of the issues described above, as
well as other possible issues.
SUMMARY
In one advantageous embodiment, a method for monitoring a runway is
provided. Data is received about the runway from a number of
sensors associated with an aircraft while the aircraft performs an
operation on the runway. A number of conditions are identified for
the runway using the data received from the number of sensors.
In another illustrative embodiment, an apparatus for monitoring a
runway is provided. A number of sensors are associated with an
aircraft. The number of sensors is configured to generate data
about a runway while the aircraft performs an operation on the
runway. The apparatus also comprises a computer system in the
aircraft. The computer system is configured to receive the data
from the number of sensors and identify a number of conditions for
the runway using the data received from the number of sensors.
The features, functions, and advantages can be achieved
independently in various embodiments of the present disclosure or
may be combined in yet other embodiments in which further details
can be seen with reference to the following description and
drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
The novel features believed characteristic of the advantageous
embodiments are set forth in the appended claims. The advantageous
embodiments, however, as well as a preferred mode of use, further
objectives and advantages thereof, will best be understood by
reference to the following detailed description of an advantageous
embodiment of the present disclosure when read in conjunction with
the accompanying drawings, wherein:
FIG. 1 is an illustration of a monitoring environment in accordance
with an advantageous embodiment;
FIG. 2 is an illustration of a data processing system in accordance
with an advantageous embodiment;
FIG. 3 is an illustration of a monitoring environment in accordance
with another advantageous embodiment;
FIG. 4 is an illustration of a number of conditions in accordance
with an advantageous embodiment;
FIG. 5 is an illustration of data in accordance with an
advantageous embodiment;
FIG. 6 is an illustration of a data flow for a monitoring
environment in accordance with an advantageous embodiment;
FIG. 7 is an illustration of a graphical user interface presenting
a navigation chart with a number of conditions for a runway in
accordance with an advantageous embodiment;
FIG. 8 is an illustration of another graphical user interface
presenting a runway in accordance with an advantageous
embodiment;
FIG. 9 is an illustration of a flowchart of a process for
monitoring a runway in accordance with an advantageous embodiment;
and
FIG. 10 is an illustration of a flowchart of an additional process
for monitoring a runway in accordance with an advantageous
embodiment.
DETAILED DESCRIPTION
Referring now to FIG. 1, an illustration of a monitoring
environment is depicted in accordance with an advantageous
embodiment. In this illustrative example, monitoring environment
100 comprises aircraft 102 and runway 103. Aircraft 102 is in the
process of landing on runway 103 in this illustrative example. In
other illustrative examples, aircraft 102 may be taxiing or taking
off from runway 103.
As depicted in this example, aircraft 102 has wheels 104, 105, and
106, fuselage 108, wing 110, another wing (not shown), and tail
112. Further, number of sensors 114 is associated with aircraft
102. A first component may considered to be associated with a
second component by being secured to the second component, bonded
to the second component, fastened to the second component, and/or
connected to the second component in some other suitable manner.
The first component also may be connected to the second component
through using a third component. The first component may also be
considered to be associated with the second component by being
formed as part of and/or an extension of the second component.
In these examples, number of sensors 114 is connected to the
underside of fuselage 108 of aircraft 102. Number of sensors 114
generates data. Data may be generated by number of sensors 114
periodically or constantly. In this advantageous embodiment, the
data is imaging data. However, the data may also comprise at least
one of radar data, light detection and ranging data (LIDAR), camera
data, infrared data, and other suitable types of data.
As used herein, the phrase "at least one of", when used with a list
of items, means that different combinations of one or more of the
listed items may be used and only one of each item in the list may
be needed. For example, "at least one of item A, item B, and item
C" may include, for example, without limitation, item A or item A
and item B. This example also may include item A, item B, and item
C, or item B and item C.
In these illustrative examples, number of sensors 114 may be
pointed in direction 116. Direction 116 is pointed towards wheel
104. Number of sensors 114 generates data for direction 116. In
other advantageous embodiments, number of sensors 114 may be
pointed towards runway 103 under and in front of aircraft 102 or in
some other suitable direction.
In this advantageous embodiment, computer system 115 is located
onboard aircraft 102. Computer system 115 receives data from number
of sensors 114. This data received from number of sensors 114 may
contain an indication of standing water 118 on runway 103. In
response to receiving data indicating standing water 118, computer
system 115 may identify standing water 118 as a condition affecting
runway 103. Computer system 115 may then send an identification of
the condition to a location remote to the aircraft. In some
advantageous embodiments, the location is a second aircraft or an
air traffic controller. However, in other advantageous embodiments,
the location is a surface friction database.
Computer system 115 onboard aircraft 102 may identify other
conditions using additional input, such as a braking distance of
aircraft 102 during landing being greater than a specified
distance. In other advantageous embodiments, a condition on runway
103 is detected when computer system 115 detects that the
directional vector of wheel 104 differs from the directional vector
of aircraft 102. A directional vector has a direction in which an
object is facing and/or moving in these illustrative examples. As
one specific example, a difference in the directional vectors for
wheel 104 and aircraft 102 may indicate skidding.
The illustration of monitoring environment 100 in FIG. 1 is not
meant to imply physical or architectural limitations to the manner
in which different features may be implemented. Other components in
addition to and/or in place of the ones illustrated may be used.
Some components may be unnecessary in some advantageous
embodiments. Also, the elements are presented to illustrate some
functional components. One or more of these elements may be
combined and/or divided into different elements when implemented in
different advantageous embodiments.
For example, number of sensors 114 may be associated with another
part of aircraft 102, such as wing 110, rather than the underside
of fuselage 108 of aircraft 102. Additionally, computer system 115
may identify a number of conditions for runway 103 in addition to
or in place of standing water 118. For example, without limitation,
the number of conditions identified may include ice, slush,
indentations, debris, plant growth that extends onto runway 103,
and/or other types of conditions.
Turning now to FIG. 2, an illustration of a data processing system
is depicted in accordance with an advantageous embodiment. In this
illustrative example, data processing system 200 may be used to
implement computer system 115 onboard aircraft 102 in FIG. 1. As
depicted, data processing system 200 includes communications fabric
202, which provides communications between processor unit 204,
memory 206, persistent storage 208, communications unit 210,
input/output (I/O) unit 212, and display 214.
Processor unit 204 serves to execute instructions for software that
may be loaded into memory 206. Processor unit 204 may be a set of
one or more processors or may be a multi-processor core, depending
on the particular implementation. Further, processor unit 204 may
be implemented using one or more heterogeneous processor systems,
in which a main processor is present with secondary processors on a
single chip. As another illustrative example, processor unit 204
may be a symmetric multi-processor system containing multiple
processors of the same type.
Memory 206 and persistent storage 208 are examples of storage
devices 216. A storage device is any piece of hardware that is
capable of storing information, such as, for example, without
limitation, data, program code in functional form, and/or other
suitable information either on a temporary basis and/or a permanent
basis. Memory 206, in these examples, may be, for example, a random
access memory or any other suitable volatile or non-volatile
storage device. Persistent storage 208 may take various forms,
depending on the particular implementation. For example, persistent
storage 208 may contain one or more components or devices. For
example, persistent storage 208 may be a hard drive, a flash
memory, a rewritable optical disk, a rewritable magnetic tape, or
some combination of the above. The media used by persistent storage
208 may be removable. For example, a removable hard drive may be
used for persistent storage 208.
Communications unit 210, in these examples, provides for
communication with other data processing systems or devices. In
these examples, communications unit 210 is a network interface
card. Communications unit 210 may provide communications through
the use of either or both physical and wireless communications
links.
Input/output unit 212 allows for the input and output of data with
other devices that may be connected to data processing system 200.
For example, input/output unit 212 may provide a connection for
user input through a keyboard, a mouse, and/or some other suitable
input device. Further, input/output unit 212 may send output to a
printer. Display 214 provides a mechanism to display information to
a user.
Instructions for the operating system, applications, and/or
programs may be located in storage devices 216, which are in
communication with processor unit 204 through communications fabric
202. In these illustrative examples, the instructions are in a
functional form on persistent storage 208. These instructions may
be loaded into memory 206 for execution by processor unit 204. The
processes of the different embodiments may be performed by
processor unit 204 using computer implemented instructions, which
may be located in a memory, such as memory 206.
These instructions are referred to as program code, computer usable
program code, or computer readable program code that may be read
and executed by a processor in processor unit 204. The program
code, in the different embodiments, may be embodied on different
physical or computer readable storage media, such as memory 206 or
persistent storage 208.
Program code 218 is located in a functional form on computer
readable media 220 that is selectively removable and may be loaded
onto or transferred to data processing system 200 for execution by
processor unit 204. Program code 218 and computer readable media
220 form computer program product 222. In one example, computer
readable media 220 may be computer readable storage media 224 or
computer readable signal media 226. Computer readable storage media
224 may include, for example, an optical or magnetic disk that is
inserted or placed into a drive or other device that is part of
persistent storage 208 for transfer onto a storage device, such as
a hard drive, that is part of persistent storage 208. Computer
readable storage media 224 also may take the form of a persistent
storage, such as a hard drive, a thumb drive, or a flash memory
that is connected to data processing system 200. In some instances,
computer readable storage media 224 may not be removable from data
processing system 200.
Alternatively, program code 218 may be transferred to data
processing system 200 using computer readable signal media 226.
Computer readable signal media 226 may be, for example, a
propagated data signal containing program code 218. For example,
computer readable signal media 226 may be an electromagnetic
signal, an optical signal, and/or any other suitable type of
signal. These signals may be transmitted over communications links,
such as wireless communications links, an optical fiber cable, a
coaxial cable, a wire, and/or any other suitable type of
communications link. In other words, the communications link and/or
the connection may be physical or wireless in the illustrative
examples.
In some advantageous embodiments, program code 218 may be
downloaded over a network to persistent storage 208 from another
device or data processing system through computer readable signal
media 226 for use within data processing system 200. For instance,
program code stored in a computer readable storage media in a
server data processing system may be downloaded over a network from
the server to data processing system 200. The data processing
system providing program code 218 may be a server computer, a
client computer, or some other device capable of storing and
transmitting program code 218.
The different components illustrated for data processing system 200
are not meant to provide architectural limitations to the manner in
which different embodiments may be implemented. The different
advantageous embodiments may be implemented in a data processing
system including components in addition to or in place of those
illustrated for data processing system 200. Other components shown
in FIG. 2 can be varied from the illustrative examples shown. The
different embodiments may be implemented using any hardware device
or system capable of executing program code. As one example, data
processing system 200 may include organic components integrated
with inorganic components and/or may be comprised entirely of
organic components excluding a human being. For example, a storage
device may be comprised of an organic semiconductor.
As another example, a storage device in data processing system 200
is any hardware apparatus that may store data. Memory 206,
persistent storage 208, and computer readable media 220 are
examples of storage devices in a tangible form.
In another example, a bus system may be used to implement
communications fabric 202 and may be comprised of one or more
buses, such as a system bus or an input/output bus. Of course, the
bus system may be implemented using any suitable type of
architecture that provides for a transfer of data between different
components or devices attached to the bus system. Additionally, a
communications unit may include one or more devices used to
transmit and receive data, such as a modem or a network adapter.
Further, a memory may be, for example, memory 206 or a cache such
as found in an interface and memory controller hub that may be
present in communications fabric 202.
Turning now to FIG. 3, an illustration of a monitoring environment
is depicted in accordance with another advantageous embodiment.
Monitoring environment 300 is an example of one implementation of
monitoring environment 100 in FIG. 1. As depicted, monitoring
environment includes monitoring system 301. Monitoring system 301
may be comprised of aircraft 302 and/or location 303 remote to
aircraft 302.
In this illustrative example, monitoring system 301 monitors
conditions for runway 304 while aircraft 302 is performing an
operation on runway 304. Runway 304 may comprise a runway, a
taxiway, or any other suitable surface for moving aircraft while on
the ground. The operation performed by aircraft 302 on runway 304
may be one of landing on runway 304, taking off from runway 304,
taxiing on runway 304, or some other operation.
As depicted, aircraft 302 has computer system 306 and number of
sensors 308 associated with aircraft 302.
Computer system 306 is an example of one implementation for
computer system 115 onboard aircraft 302. Further, computer system
306 may be implemented using data processing system 200 in FIG. 2.
Computer system 306 may be located onboard aircraft 302, partially
onboard aircraft 302, or in a location elsewhere but accessible to
systems onboard aircraft 302.
Computer system 306 receives data 310 from number of sensors 308.
In this illustrative example, data 310 includes at least one of
imaging data, radar data, light detection and ranging data (LIDAR),
camera data, infrared data, and other suitable types of data.
In these advantageous embodiments, number of sensors 308 is
associated with aircraft 302 by being attached to underside 312 of
fuselage 314 of aircraft 302. In other advantageous embodiments,
number of sensors 308 are not associated with aircraft 302 and are
instead associated with runway 304 and/or the area surrounding
runway 304. For example, number of sensors 308 may be located on
the ground. Number of sensors 308 may include, for example, without
limitation, at least one of a radar detector, a camera, a video
camera, an infrared detector, and some other suitable type of
sensor.
In this illustrative example, number of sensors 308 may be pointed
towards wheel 318 of aircraft 302 to generate data 310 regarding
runway 304. However, in other illustrative examples, number of
sensors 308 may be pointed in any direction that allows number of
sensors 308 to generate data 310 regarding runway 304.
Computer system 306 uses data 310 received from number of sensors
308 to identify number of conditions 319 for runway 304. Number of
conditions 319 includes, for example, without limitation, at least
one of standing water, snow, slush, ice, an inconsistency in the
runway, a debris, an indentation, a plant growth extending onto the
runway, and other types of conditions.
Data 310 may include directional vector 326 of wheel 318 and/or
directional vector 330 of aircraft 302. Computer system 306 may
identify condition 320 in number of conditions 319 on runway 304
when directional vector 330 of aircraft 302 differs from
directional vector 326 of wheel 318. For example, if directional
vector 326 of wheel 318 is aligned with directional guidance lines
on runway 304 but directional vector 330 of aircraft 302 is
identified as being towards the right side of runway 304, computer
system 306 may identify condition 320 as skidding.
In another advantageous embodiment, computer system 306 may
identify condition 320 for runway 304 if braking distance 322 is
greater than specified distance 324. Braking distance 322 may be
determined, for example, while aircraft 302 is decelerating on
runway 304 during a landing operation. In these examples, braking
distance 322 is the distance used by aircraft 302 to decelerate
from the speed at which aircraft 302 contacts runway 304 during a
landing operation to a selected speed. The selected speed may be
zero or some other speed specified by an operator of aircraft 302.
In one advantageous embodiment, the selected speed is a speed used
for taxiing.
Once computer system 306 identifies number of conditions 319,
computer system 306 presents number of conditions 319 on a display
device 336 in computer system 306. Display device 336 may be, for
example, a display screen, a touchscreen, or some other suitable
type of display device.
As one illustrative example, number of conditions 319 is displayed
on navigational chart 340 on display device 336. In this manner,
computer system 306 updates navigational chart 340 with number of
conditions 319 for runway 304 for use by an operator of aircraft
302. Number of conditions 319 may be displayed on navigational
chart 340 as information points associated with runway 304 or as a
list of conditions present in a geographic area of navigational
chart 340.
Computer system 306 also sends number of conditions 319 to location
303 remote to aircraft 302. Location 303 may be a second aircraft,
such as aircraft 342, air traffic controller 346, surface friction
database 348, or some other suitable location. Number of conditions
319 may be sent to location 303 by computer system 306 using
wireless communications system 350.
In some advantageous embodiments, aircraft 342 is an aircraft
within a particular distance of runway 304. In other advantageous
embodiments, aircraft 342 is executing a flight plan that involves
landing on runway 304. Aircraft 342 may use number of conditions
319 to update a navigational chart aboard aircraft 342 or to alert
the flight crew aboard aircraft 342 of number of conditions
319.
Location 303 may also be air traffic controller 346. Air traffic
controller 346 may receive number of conditions 319 as a list or as
information points on a navigational chart. Location 303 may also
be surface friction database 348. Computer system 306 may send
number of conditions 319 to surface friction database 348 such that
surface friction database 348 is updated to store number of
conditions 319.
In one advantageous embodiment, surface friction database 348
contains a measurement of friction at numerous points on the
surface of runway 304. The measurement may be based on number of
conditions 319. For example, when number of conditions 319
indicates the presence of ice on runway 304, surface friction
database 348 may be updated to reflect reduced surface friction on
runway 304. Surface friction database 348 may be stored at a
regulatory authority, such as the Federal Aviation Administration
in the United States.
The illustration of monitoring environment 300 in FIG. 3 is not
meant to imply physical or architectural limitations to the manner
in which different features may be implemented. Other components in
addition to and/or in place of the ones illustrated may be used.
Some components may be unnecessary in some advantageous
embodiments. Also, the blocks are presented to illustrate some
functional components. One or more of these blocks may be combined
and/or divided into different blocks when implemented in different
advantageous embodiments.
For example, directional vector 326 may be detected with respect to
more than one wheel 318. Additionally, number of sensors 308 may be
located in multiple locations around aircraft 302. For example, a
sensor may be located in the nose area of aircraft 302 and pointed
forward towards runway 304. Another sensor in number of sensors 308
may be located near the aft wheels of aircraft 302 and pointed
toward runway 304.
Some elements of monitoring environment 300 may be located onboard
aircraft 302 while other elements of monitoring environment 300 are
located offboard aircraft 302. For example, in some advantageous
embodiments, all components of computer system 306 are located on
aircraft 302. In other advantageous embodiments, computer system
306 is not located onboard aircraft 302. For example, computer
system 306 may be located at an airport or an airline. In yet other
advantageous embodiments, some components of computer system 306
are located onboard aircraft 302 and other components of computer
system 306 are located elsewhere, such as at an airport or an
airline headquarters. Likewise, other elements of monitoring
environment 300 may be located onboard aircraft 302 or elsewhere in
different advantageous embodiments.
Turning now to FIG. 4, an illustration of a number of conditions is
depicted in accordance with an advantageous embodiment. Number of
conditions 400 is an example of one implementation of number of
conditions 319 in FIG. 3. Number of conditions 400 may be
identified by a number of sensors, such as number of sensors 308 in
FIG. 3.
In this illustrative example, number of conditions 400 includes
standing water 402, snow 404, slush 406, ice 408, inconsistency
410, debris 412, indentation 414, and plant growth 416. Standing
water 402 is any collection of water on the runway being monitored.
The water may be draining or may be stagnant.
With respect to each of snow 404, slush 406, and ice 408, a sensor
may be configured to identify number of conditions 400 only when a
particular amount of accumulation has occurred on the runway, or
when any accumulation has occurred.
Inconsistency 410 is any deviation from the design of the surface
of the runway. For example, inconsistency 410 may be a pothole in
the runway. An example of debris 412 is a piece of rubber from the
tire of another aircraft. Indentation 414 is a groove or dip in the
surface of the runway. In some advantageous embodiments,
indentation 414 is caused by the wear associated with frequent use
of the runway by aircraft.
Plant growth 416 may be any plant that extends onto the surface of
the runway. In some advantageous embodiments, a computer system may
be configured to identify a condition of plant growth 416 only when
plant growth 416 extends onto the runway by more than a specified
distance. For example, grass that extends onto the runway by more
than about two linear feet may be identified as a condition
affecting the runway.
Of course, number of conditions 400 may include other conditions
418. Other conditions 418 are any additional conditions in number
of conditions 400 that are identified by a monitoring system, such
as monitoring system 301. For example, other conditions 418 may
include an uneven surface on the runway, cracks in the runway, or
parts of a runway that have moved due to a seismic event.
Turning now to FIG. 5, an illustration of data is depicted in
accordance with an advantageous embodiment. Data 500 is an example
of one implementation of data 310 in FIG. 3. Data 500 may be
received by a computer system from a number of sensors, such as
number of sensors 308 in FIG. 3. Data 500 may comprise at least one
of imaging data 501, radar data 502, light detection and ranging
data 504, camera data 506, and infrared data 508.
Of course, data 500 may also include other data 510. Other data 510
is data from another source. For example, other data 510 may
include data for conditions that are part of a user input.
With reference now to FIG. 6, an illustration of a data flow for a
monitoring environment is depicted in accordance with an
advantageous embodiment. The data flow illustrated in FIG. 6 is for
a monitoring environment, such as monitoring environment 100 in
FIG. 1 and/or monitoring environment 300 in FIG. 3.
In this illustrative example, sensor controller 600 may be
implemented in a sensor, such as a sensor in number of sensors 308
in FIG. 3. Sensor 636 is a device that measures one or more
properties and converts the measurement to data. For example,
sensor 636 may generate imaging data and/or temperature data. In
some advantageous embodiments, sensor 636 comprises a number of
sensors 636. As used herein, "a number of" an element means one or
more of the element. For example, "a number of sensors 636" means
one or more sensors 636.
Sensor controller 600 controls the operation of sensor 636. Sensor
controller 600 engages or disengages sensor 636, and/or controls a
mode of sensor 636. For example, sensor controller 600 may set
sensor 636 to a scanning mode. In a scanning mode, sensor 636 may
generate data of a particular type and then generate data of a
different type. The change of type may be periodic or determined
based on the data being generated. For example, in advantageous
embodiments in which sensor 636 comprises multiple sensors 636,
sensor controller 600 may cause sensors 636 to generate temperature
data for 10 seconds, and then generate imaging data for 10 seconds.
In another such advantageous embodiment, sensor controller 600 may
schedule a thermocouple sensor 636 to operate for ten seconds, and
then schedule a camera sensor 636 to operate for ten seconds.
Alternatively, sensor controller 600 may cause sensor 636 to
generate imaging data until a condition occurs, such as landing of
the aircraft is completed. Sensor controller 600 generates data
602. Data 602 may be, for example, data 310 in FIG. 3 and/or data
500 in FIG. 5.
Sensor controller 600 sends data 602 to data processing system 604.
Data processing system 604 may be implemented using data processing
system 200 in FIG. 2 and/or computer system 306 in FIG. 3. As
depicted, source data manager 605, reasoner 608, output manager
610, and display controller 612 are implemented within data
processing system 600. Source data manager 605 receives data 602
from sensor controller 600. Source data manager 605 may store data
602 and/or make data 602 available to be processed by algorithms
606 running on data processing system 604.
Algorithms 606 perform a number of operations using data 602 to
generate data. In this advantageous embodiment, algorithms 606 are
algorithms that identify a number of conditions present on the
runway. The number of conditions may be an example implementation
of number of conditions 400 in FIG. 4. For example, algorithms 606
may be a fast Fourier transform or digital signal filtering or
wavelets. After being processed by algorithms 606 running on data
processing system 604, data 614 is sent to reasoner 608. Reasoner
608 identifies a number of conditions present on the runway using
data 614. The number of conditions may be, for example, number of
conditions 400 in FIG. 4. Reasoner 608 also determines whether
adjustments are to be made to sensor controller 600. For example,
reasoner 608 may determine that sensor controller 600 is configured
to be too sensitive. Thus, sensor controller 600 may decrease
sensitivity of sensor 636. In some advantageous embodiments,
reasoner 608 uses situational awareness 616 to identify the number
of conditions within data 614.
Situational awareness 616 is data that describes the physical
environment being monitored. In some advantageous embodiments,
situational awareness 616 comprises aircraft operational data
and/or weather data. For example, situational awareness 616 may
comprise any combination of temperature data, weather data,
airspeed, weight on wheels of the aircraft, angle of attack of the
aircraft, weather forecast data, or other suitable environmental
data.
Reasoner 608 sends the number of conditions identified to output
manager 610. Output manager 610 sends the number of conditions to
display controller 612 for presentation. Display controller 612
presents the number of conditions on display device 618. In some
illustrative examples, the number of conditions may be presented on
a navigational chart displayed on display device 618.
Output manager 610 also sends the number of conditions to receiver
620 using a wireless communications system. In other advantageous
embodiments, output manager 610 may use a wired communications
system. Receiver 620 may be in a location remote to the aircraft
having data processing system 604. For example, receiver 620 may be
in a second aircraft or an air traffic controller.
Receiver 620 sends the number of conditions to data manager 622.
Data manager 622 sends the number of conditions to historical data
warehouse 624. Historical data warehouse 624 is a database storing
data about conditions for the runway over a period of time, such
as, for example, a number of months or a number of years. Data
manager 622 also retrieves data from historical data warehouse 624.
Data manager 622 sends information in the form of the data
retrieved from historical data warehouse 624 and the number of
conditions received from receiver 620 to prognostic algorithms
626.
Prognostic algorithms 626 use the data received from data manager
622 to make predictions about the number of conditions present on
the runway or other conditions that may develop on the runway. For
example, prognostic algorithms may be used to determine that ice
accumulation on the runway will increase by one inch every two
hours, based on the data received from data manager 622. In another
advantageous embodiment, prognostic algorithms may generate a
prediction that a crack present on the runway will grow at a
particular rate. The predictions generated by prognostic algorithms
626 are sent back to data manager 622. Data manager 622 sends these
predictions and/or the number of conditions received from receiver
620 to display controller 628.
Display controller 628 presents the information received on display
device 630, display device 632, and display device 634. Display
devices 630, 632, and 634 may be located in the same location or
different locations. In some advantageous embodiments, display
device 630 is located in a cockpit of the aircraft, display device
632 is located in an air traffic control tower, and display device
634 may be located at an airline operations center. Of course,
additional display controllers 628 may be present to present data
on display devices 630, 632, and 634 in some advantageous
embodiments.
With reference now to FIG. 7, an illustration of a graphical user
interface presenting a navigational chart with a number of
conditions for a runway is depicted in accordance with an
advantageous embodiment. Navigational chart 700 is an example
implementation of navigational chart 340 in FIG. 3. Navigational
chart 700 may be presented using a display device, such as display
device 336 in FIG. 3. In these examples, navigational chart 700
presents a runway at an airport. However, navigational chart 700
may present other information in other advantageous
embodiments.
Runway 702 is located on navigational chart 700. Runway 702
represents a real world runway that has a number of conditions
present on the real world runway. Runway 702 presents the number of
conditions present on the real world runway at the time
navigational chart 700 is presented. The number of conditions may
be an example implementation of number of conditions 400 in FIG.
4.
The number of conditions present on runway 702 at the time
navigational chart 700 is presented are shown on runway 704. Runway
704 presents additional detail about runway 702 and is also
presented using a display device. Specifically, runway 704 presents
the number of conditions present on the real world runway
represented by runway 702 at the time navigational chart 700 is
presented. The number of conditions presented on runway 704 may be
identified by an aircraft in which navigational chart 700 is being
presented. In other advantageous embodiments, the number of
conditions presented on runway 704 are received from another
aircraft, such as aircraft 302 in FIG. 3.
Runway 704 is presented with a number of conditions. The number of
conditions, in these examples, comprises slush 706, cracks 708, ice
710, standing water 712, pothole 714, and section 716. Of course,
additional types of conditions may be presented in other
advantageous embodiments. For example, plant overgrowth onto runway
704 or snow present on runway 704 may be presented in other
advantageous embodiments. In an advantageous embodiment in which
snow is presented on runway 704, a different visual indicator may
be used for snow that is compressed more than a specified amount.
The number of conditions are presented on runway 704 in the
locations in which they were identified on runway 704. In other
words, the location at which the number of conditions are presented
represents the location of each of the number of conditions on the
actual runway being represented by runway 704.
Slush 706 represents a mixture of snow and water. Cracks 708 are
inconsistencies in the surface of runway 704. The inconsistencies
may be caused by use of runway 704 by one or more aircraft, or
another object impacting runway 704. Ice 710 represents frozen
water present on runway 704. Standing water 712 represents liquid
water on runway 704 that is stagnant and/or not draining from
runway 704 at a particular rate. Pothole 714 is an inconsistency in
runway 704 that is greater than a particular length and/or width.
Section 716 represents a section of runway 704 that exceeds a
particular degree or size of inconsistency in runway 704. In this
advantageous embodiment, section 716 is presented with a warning
not to use section 716 of runway 704. The warning may indicate to a
pilot that section 716 of the real world runway represented by
runway 704 should not be used during takeoff, taxiing, or landing
of an aircraft. Section 716 may also be identified using another
source, such as being designated by a user input.
Of course, runway 704 may be presented a number of different ways,
and the depiction of runway 704 should not be construed as
limiting. In other advantageous embodiments, runway 704 is
presented with various color-coded areas that indicate a severity
of an inconsistency. For example, one area of runway 704 may be
presented in red to indicate that the area of runway 704 should not
be used by an aircraft, and another area of runway 704 may be
presented in blue to indicate that standing water is located in the
blue area of the actual runway represented by runway 704.
With reference now to FIG. 8, an illustration of another graphical
user interface presenting a runway is depicted in accordance with
an advantageous embodiment. Runway 800 may be another example
implementation of runway 704 in FIG. 7. Runway 800 may be presented
on and/or with navigational chart 700 or in another graphical user
interface.
Areas 802, 804, 806, and 808 indicate that data has been generated
for the corresponding portions of runway 800. As used herein, the
corresponding portions of runway 800 for areas 802, 804, 806, and
808 means the portions of the actual runway represented by runway
800 that are located substantially within areas 802, 804, 806, and
808 on runway 800. The data may comprise a number of conditions,
such as number of conditions 319 in FIG. 3.
In some advantageous embodiments, areas 802, 804, 806, and 808 are
presented in the order that the data was generated. For example,
area 804 is presented as faded and underneath areas 806 and 808.
Presenting area 804 underneath areas 806 and 808 indicates that the
data represented by area 804 was generated prior to areas 806 and
808. In some advantageous embodiments, presenting area 804 as faded
indicates that the data contained in area 804 was generated more
than a specified amount of time prior to runway 800 being
presented.
Portions 810 and 812 are presented within area 802. Portion 810
indicates that a condition of ice is present in the corresponding
portion of runway 800. Portion 812 indicates that no condition is
present in the corresponding portion of runway 800.
Portions 814, 816, and 818 are presented within area 808. Portion
814 indicates that no condition is present in the corresponding
portion of runway 800. Portion 816 indicates that standing water
was identified in the corresponding portion of runway 800. Standing
water is any collection of water on the runway being monitored. The
water may be draining or may be stagnant. Portion 818 indicates
that no condition is present in the corresponding portion of runway
800.
Portions 820, 824, 826, and 828 are presented within area 806.
Portion 820 indicates that a condition of between about one and
three inches of snow was identified on the corresponding portion of
runway 800. Of course, the amount of snow in this advantageous
embodiment is an example and should not be construed as limiting.
The amount of snow indicated by portion 820 may be any amount or
range of amounts. For example, the amount of snow indicated by
portion 820 may be about two to three inches or about one to six
inches. Multiple ranges may also be present with the same or
different indicators. For example, another portion may indicate an
amount of snow between about four and six inches. The amount may be
scaled by the geographic region of runway 800 or received as a user
input.
Portion 824 indicates that a condition of ice with low friction was
identified in the corresponding portion of runway 800. In some
advantageous embodiments, portions 820 and 824 are presented with
colors that transition into each other. In such an advantageous
embodiment, both conditions of ice with low friction and between
about one and three inches of snow may be present in the
corresponding portion of runway 800. Portion 826 indicates that no
condition is present in the corresponding portion of runway 800.
Portion 828 indicates that a condition of standing water is present
in the corresponding portion of runway 800.
Portions 822, 832, 834, and 836 are presented within area 804.
Portion 822 indicates that a condition of standing water was
identified on the corresponding portion of runway 800. Portion 836
indicates that a condition of ice with low friction was identified
in the corresponding portion of runway 800. In some advantageous
embodiments, portions 822 and 836 are presented with colors that
transition into each other. In such an advantageous embodiment,
both conditions of ice with low friction and standing water may be
present in the corresponding portion of runway 800. Portion 832
indicates that no condition is present in the corresponding portion
of runway 800. Portion 834 indicates that standing water was
identified in the corresponding portion of runway 800.
With reference now to FIG. 9, an illustration of a flowchart of a
process for monitoring a runway is depicted in accordance with an
advantageous embodiment. The process illustrated in FIG. 9 may be
implemented in monitoring environment 300 for runway 304 in FIG.
3.
The process begins by receiving data about the runway from a number
of sensors associated with an aircraft while the aircraft is using
the runway (operation 900). In operation 900, the data received
from the number of sensors may include, for example, without
limitation, imaging data, radar data, light detection and ranging
data (LIDAR), camera data, infrared data, and/or other suitable
types of data.
Thereafter, the process identifies a number of conditions for the
runway using the data received from the number of sensors
(operation 902), with the process terminating thereafter. In
operation 902, the number of conditions include at least one of
standing water, snow, slush, ice, an inconsistency in the runway,
debris on the runway, an indentation, a plant growth extending onto
the runway, and some other suitable runway condition.
Turning now to FIG. 10, an illustration of a flowchart of an
additional process for monitoring a runway is depicted in
accordance with an advantageous embodiment. The process may be
performed in monitoring environment 300 by computer system 306 in
FIG. 3.
The process begins by collecting data (operation 1000). The data
may be collected by a number of sensors, such as number of sensors
308 in FIG. 3. The data collected may be, for example, altitude of
the aircraft, whether the aircraft is taking off or landing, and
whether the aircraft is executing a flight plan.
The process then receives the data (operation 1002). The data that
is received is at least some of the data collected in operation
1000. In operation 1002, the data may be combined with other data,
such as situational awareness 616 in FIG. 6. The data may include
any combination of temperature data, weather data, weather
forecasts, airspeed of the aircraft, weight on wheels of the
aircraft, and angle of attack of the aircraft.
The process then filters the data (operation 1004). Filtering the
data may comprise removing noise from the data, and checking
validity of the data. Checking validity of the data may comprise
determining whether the data is within a predetermined range for
the particular type of data. Data exceeding the prespecified limits
may be discarded. For example, temperature data that exceeds about
250 degrees Fahrenheit may be discarded.
The process then extracts features from the data (operation 1006).
Extracting features from the data comprises performing a transform
on the data. For example, the data may be transformed using a fast
Fourier transform and/or other suitable digital signal processing.
The transform may indicate a frequency of a particular value or
series of values that occurs in the data.
The process then identifies conditions within the features
(operation 1008). In some advantageous embodiments, the features
extracted in operation 1006 are represented by one or more numbers.
The numbers may be compared with predetermined or specified values
to determine whether a particular type of data indicates the
presence of a type of condition on the runway. For example, the
numeric value extracted in operation 1006 with respect to snow
measurement may be identified as the presence of two inches of snow
on a particular portion of the runway.
The process then updates a database with the number of conditions
(operation 1010). The database may contain a number of conditions
for a number of runways. In one advantageous embodiment, the
database is a surface friction database. The surface friction
database may be maintained by an airport, an airline, a regulatory
authority, or any other suitable party. The process may update the
surface friction database with the surface friction detected on the
runway at the time the data was generated and/or a number of other
conditions present on the runway at the time the data was
generated. The process terminates thereafter.
The process then presents the conditions on a display (operation
1012). The display may be located onboard the aircraft, onboard
another aircraft, in an air traffic control area, at an airline
operations center or any other suitable location. The conditions
may be presented on a navigational chart, in some advantageous
embodiments, such as navigational chart 700 in FIG. 7.
The flowcharts and block diagrams in the different depicted
embodiments illustrate the architecture, functionality, and
operation of some possible implementations of apparatus and methods
in different advantageous embodiments. In this regard, each block
in the flowcharts or block diagrams may represent a module,
segment, function, and/or a portion of an operation or step. In
some alternative implementations, the function or functions noted
in the block may occur out of the order noted in the figures. For
example, in some cases, two blocks shown in succession may be
executed substantially concurrently, or the blocks may sometimes be
executed in the reverse order, depending upon the functionality
involved. For example, operation 1012 may be performed prior to
operation 1010 or at the same time as operation 1012. Also, other
blocks may be added in addition to the illustrated blocks in a
flowchart or block diagram.
The description of the different advantageous embodiments has been
presented for purposes of illustration and description, and is not
intended to be exhaustive or limited to the embodiments in the form
disclosed. Many modifications and variations will be apparent to
those of ordinary skill in the art. Further, different advantageous
embodiments may provide different advantages as compared to other
advantageous embodiments. The embodiment or embodiments selected
are chosen and described in order to best explain the principles of
the embodiments, the practical application, and to enable others of
ordinary skill in the art to understand the disclosure for various
embodiments with various modifications as are suited to the
particular use contemplated.
* * * * *